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This paper focuses on the possible roles of aggregators in the European electricity markets and the challenges and opportunities they face in participating in different market segments. Demand response (DR) is becoming increasingly important with the growth of renewable energy, and aggregators can play a critical role in balancing supply and demand in real time. This paper provides an overview of prices in electricity markets in which DR aggregators can participate and provides recommendations for aggregators regarding which markets to focus on. However, the regulatory framework for aggregators is still evolving in Europe, creating challenges for them to navigate different market designs, regulatory frameworks, and pricing mechanisms. Through a combination of literature review and data analysis, this paper aims to provide insights for aggregators on how to maximize profits and minimize risks in the European electricity market. The article achieves this by conducting an extensive analysis of various markets, comparing their essential attributes relevant to the functioning of aggregators. [ABSTRACT FROM AUTHOR]

The current formal common denominator of the electricity supply system in Europe has been the Harmonized Electricity Market Role Model (HEMRM) set up by ENTSO-E, ebIX, and EFET at the turn of the millennium; it introduced the concept of de-coupling and the vertical structuring of the system into the previously vertically integrated system. Since then, within demonstration projects, the system has been undergoing further changes in a controlled environment, generating bottom-up energy, caused by new technologies, business models, and new players, and extending the concept of the system to the level of energy communities and prosumers. Therefore, this paper proposes a coherent approach to the extension of HEMRM to the lowest levels in both the grid and market segments—full harmonization. This entails further structuring of both segments downwards and applying the principles of vertically nested subsystems—a system of systems approach—to a unit functional level of the electricity system, which can be the prosumer itself. At the lowest levels, the de-coupled system becomes coupled; additionally, it cross-sects with other energy vectors. Complete harmonization reduces the number of system and market segments and represents system standardization, leading to both subsystem and system-wide optimization. Prerequisites for it include the automated trading of flexibilities by the prosumers and implicit trading of energy transfer capacities along the distribution grids. The energy reservoirs, implicit and explicit, short-term, and long-term, play a vital role in techno-economic balancing. [ABSTRACT FROM AUTHOR]

Moving towards regional Supergrids, an increasing number of interconnections are formed by High Voltage Direct Current (HVDC) lines. Currently, in most regions, HVDC losses are not considered in market operations, resulting in additional costs for Transmission System Operators (TSOs). Nordic TSOs have proposed the introduction of HVDC loss factors in the market clearing algorithm, to account for the cost of losses and avoid HVDC flows between zones with zero price difference. In this paper, we introduce a rigorous framework to assess the introduction of loss factors, in particular HVDC loss factors, in nodal and zonal pricing markets. First, we focus on the identification of an appropriate loss factor. We propose and compare three different models: constant, linear, and piecewise linear. Second, we introduce formulations to include losses in market clearing algorithms. Carrying numerical tests for a whole year, we find that accounting only for HVDC or AC losses may lead to lower social welfare for a non-negligible amount of time. To counter this, this paper introduces a framework for including both AC and HVDC losses in a zonal or nodal pricing environment. We show both theoretically and through simulations that such a framework is guaranteed to increase social welfare. [ABSTRACT FROM AUTHOR]

In this paper, we present a two-stage model of zonal electricity markets with day-ahead market clearing, and real-time re-dispatch and balancing that accounts for transmission line switching at both stages. We show how the day-ahead problem with switching can be formulated as an adaptive robust optimization problem with mixed integer recourse, and present a new algorithm for solving the adversarial max-min problem that obeys the structure of an interdiction game. We apply the model on a realistic instance of the Central Western European system, and comment on the impacts of both proactive, and reactive transmission switching on the operating costs of the system. Part I presents day-ahead models of a short-term zonal electricity market with switching, and describes our algorithmic approach for solving these models efficiently. Part II describes variants of the real-time model, and presents the results of our case study on the Central Western European market. [ABSTRACT FROM AUTHOR]

2020 was a key year for several targets in European energy and climate policy, including the requirement for European countries to deploy smart metering for at least 80% of electricity consumers. This target was set to ease the transition towards a consumer-centered and digitalized energy system. In fact, there are numerous applications that are facilitated or are directly linked to smart meters. Among others: demand response programs that enable consumers to be active in the energy market, and remote grid monitoring by the Distribution System Operator. In this paper, we analyze the initial provisions of the Third Energy Package and those of the Clean Energy Package, with particular focus on the recently approved directive on common rules for the internal market for electricity and the newly introduced smart meters specifications. We present the highlights of the national cost–benefit analyses for smart metering roll-out, focusing on the decisions made by the Member States with respect to a potential smart meter roll-out, that was targeted to be completed by 2020 and present the current situation of smart metering roll-out. We also present and categorize some of the R&I smart grid projects realized over recent years, focusing on the ones that deal with smart metering integration in order to depict the smart metering applications and technologies tested on the ground. Therefore, this paper portrays a full picture with respect to smart meters in Europe today and gives insights for monitoring smart metering roll-outs taking into account the current trends in smart metering applications. [ABSTRACT FROM AUTHOR]

During the last years, European intraday power markets have gained importance for balancing forecast errors due to the rising volumes of intermittent renewable generation. However, compared to day-ahead markets, the drivers for the intraday price process are still sparsely researched. In this paper, we propose a modelling strategy for the location, shape and scale parameters of the return distribution in intraday markets, based on fundamental variables. We consider wind and solar forecasts and their intraday updates, outages, price information and a novel measure for the shape of the merit-order, derived from spot auction curves as explanatory variables. We validate our modelling by simulating price paths and compare the probabilistic forecasting performance of our model to benchmark models in a forecasting study for the German market. The approach yields significant improvements in the forecasting performance, especially in the tails of the distribution. At the same time, we are able to derive the contribution of the driving variables. We find that, apart from the first lag of the price changes, none of our fundamental variables have explanatory power for the expected value of the intraday returns. This implies weak-form market efficiency as renewable forecast changes and outage information seems to be priced in by the market. We find that the volatility is driven by the merit-order regime, the time to delivery and the closure of cross-border order books. The tail of the distribution is mainly influenced by past price differences and trading activity. Our approach is directly transferable to other continuous intraday markets in Europe. [ABSTRACT FROM AUTHOR]

Determining contingency aware dispatch decisions by solving a security-constrained optimal power flow (SCOPF) is challenging for real-world power systems, as the high problem dimensionality often leads to impractical computational requirements. This problem becomes more severe when the SCOPF has to be solved not only for a single instance, but for multiple periods, e.g. in the context of electricity market analyses. This paper proposes an algorithm that identifies the minimal set of constraints that exactly define the space of feasible nodal injections for a given network and contingency scenarios. By internalizing the technical limits of the nodal injections and enforcing a minimal worst-case impact of contingencies to line flows, computational effort can be further improved. The case study applies and analyzes the methods on the IEEE 118 and A&M 2000 bus systems, as well as the German and European transmission systems. In all tested cases the proposed algorithm identifies at least 95% of the network and security constraints as redundant, leading to significant SCOPF solve time reductions. Scalability and practical implementation are explicitly discussed. The code and input data of the case study is published supplementary to the paper under an open-source license. [ABSTRACT FROM AUTHOR]

CROSS BOrder management of variable renewable energies and storage units enabling a transnational Wholesale market (CROSSBOW) is an EC-funded project, whose aim is to facilitate the shared use of energy resources by fostering cross-border management of variable renewable energies and storage units, enabling higher penetration of renewable energy sources (RES) whilst reducing network operational costs and improving economic benefits of clean energies and storage units. Towards these goals, CROSSBOW boosts regional cooperation among the system operators in Southeastern Europe (SEE), by deploying nine different tools to support the security coordination center (SCC) of the region. More specifically, the main CROSSBOW product, namely CROSSBOW Regional Operation Centre (CROSSBOW ROC) has proposed and demonstrated a set of functionalities for regional management and operation that enhance the existing regional structures, extending the capabilities of the already established Regional Security Coordinator (RSC) initiatives. Beyond enhancing RSC mandatory functions (including adequacy forecasts, coordinated security analysis, capacity calculations, and outage planning coordination), the ROC-BC product has developed new functions, linking the security considerations of involved TSOs with the operation of the fast-developing and harmonized electricity markets. In this paper, we investigate approaches for coordinated capacity calculation and cross-border trading via market coupling, developed within the ROC-BC product of CROSSBOW. Moreover, we present the final demonstration results as a part of ROC fundamental functionalities. Specifically, both net transfer capacity (NTC) and flow-based (FB) methods are examined and compared within a case study applying to the SEE region. The presented results demonstrate that the FB method exhibits better performance in all examined scenarios, considering three different key performance indicators (KPIs). [ABSTRACT FROM AUTHOR]

This paper provides the first EU wide analysis of the variation in Capacity Remuneration Requirements throughout Europe which aim to resolve the "missing money" problems in various member states. The findings of this analysis point to an asymmetric investment case for gas-fired peaking power plants throughout the EU. Under the assumptions of the European Commission Reference Scenario, pan-European power optimisation and investment models are specified for 2030. The results show that future investment in gas generators will depend on the availability of capacity payments. Capacity remuneration mechanisms can provide this "missing money," but we show that capacity remuneration requirements vary considerably across countries. We consider and model the impacts of country specific climate policy targets, sovereign risk, capital allowances, corporate taxes and future gas network tariffs on investor returns and therefore remuneration requirements. In the context of harmonised energy trading, this raises questions of how generation adequacy should be achieved, particularly in the context of higher penetrations of renewables. [ABSTRACT FROM AUTHOR]

Electricity markets are increasingly influenced by variable renewable energy such as wind and solar power, characterized by a pronounced weather-induced variability and imperfect predictability. As a result, the evaluation of the capacity value of variable renewable energy, i.e., its contribution to security of supply, gains importance. This paper develops a new methodology to endogenously determine the capacity value in large-scale investment and dispatch models for electricity markets. The framework allows balancing effects to be accounted for that arise due to the spatial distribution of generation capacities and interconnectors. The practical applicability of the methodology is shown with an application for wind power in Europe. We find that wind power can substantially contribute to security of supply in a decarbonized European electricity system in 2050, with regional capacity values ranging from 1-40%. Analyses that do not account for the temporal and spatial heterogeneity of the contribution of wind power to security of supply therefore lead to inefficient levels of dispatchable back-up capacity. Applying a wind power capacity value of 5% results in an overestimation of firm capacity requirements in Europe by 66 GW in 2050. This translates to additional firm capacity provision costs of 3.8 bn EUR per year in 2050, which represents an increase of 7%. [ABSTRACT FROM AUTHOR]

New generators located far from consumption centers require transmission infrastructure and increase network losses. The primary objective of this paper is to study signals that affect the location of generation investment. Such signals result from the electricity market itself and from additional regulatory instruments. We cluster them into five groups: locational electricity markets, deep grid connection charges, grid usage charges, capacity mechanisms, and renewable energy support schemes. We review the use of instruments in twelve major power systems and discuss relevant properties, including a quantitative estimate of their strength. We find that most systems use multiple instruments in parallel, and none of the identified instruments prevails. The signals vary between locations by up to 20 EUR per MWh. Such a difference is significant when compared to the levelized costs of combined cycle plants of 64-72 EUR per MWh in Europe. [ABSTRACT FROM AUTHOR]

The liberalization of energy markets worldwide during recent decades has introduced severe implications for the price formation in these markets. Especially within the European day-ahead electricity markets, increased physical connections between different market areas and a joint effort on optimizing the aggregate social welfare have led to highly connected markets. Consequently, observing the exact same hourly day-ahead prices for two or more interconnected electricity markets in Europe happens frequently. This affects the modelling of such prices and in turn the valuation of derivatives written on prices from these market areas. In this paper, we propose a joint model for day-ahead electricity prices in interconnected markets composed of a combination of transformed Ornstein–Uhlenbeck processes. We discuss the properties of the model and propose an estimation procedure based on filtering techniques. Furthermore, the properties of the model reveal that analytical prices are attainable for, e.g., forwards and spread options. [ABSTRACT FROM AUTHOR]

Featured Application: Support for policymaking in electricity balancing markets. The future power system, characterized by lower inertia, reduced programmability and more distributed architecture, will depend on prompt and reliable control systems. Quick ancillary services provided by battery energy storage systems (BESS) could be a resource in order to deliver fast and precise response to frequency events. Degrees of freedom in the design of innovative products traded on ancillary services markets give the asset manager room for developing state-of-charge (SoC) restoration mechanisms. These are necessary to effectively exploit BESS as key resources for electricity balancing. This study compares the main SoC restoration strategies. It aims to define which ones are suitable for guaranteeing the reliability of the provision and the return on the investment. A robust regulatory framework analysis describes the degrees of freedom guaranteed by the main experiences around Europe. In this paper, a BESS model with variable efficiency is used to compare the provision of Frequency Containment Reserve (FCR) with different SoC restoration strategies exploiting one or more degrees of freedom. Here, we show that the degrees of freedom are key to the reliability of provision. Among most diffused mechanisms, dead-band strategies secure the desired consistency, but require large energy flows for SoC management. Thus, BESS life and economics decrease. The strategies based on minimum available energy guarantee assured reliability while being fair with BESS life and operation costs. [ABSTRACT FROM AUTHOR]

Transitioning from fossil fuel dominated power systems to high penetrations of intermittent renewable generation is affecting classical electricity market designs. Here, a method is proposed to model and assess the absence of co-optimization of energy and reserve that prevails in the European system. Co-optimization is formulated through an optimization problem (COM), and its absence as an equilibrium problem (EQM) built on Karush-Kuhn-Tucker conditions of agents’ optimization and market clearing equations. EQM cannot be reformulated as a single optimization problem. Market distortions are identified by comparing the complementarity conditions of both models. These are then discussed on system with Feed in Premium to wind generation. Parameters in the models allow to represent different market configurations regarding: available wind generation, Feed in Premium to wind, generators’ risk aversion, and required reserve from wind generation. [ABSTRACT FROM AUTHOR]

Flow-based market coupling is a critical element of the electricity market in Europe. Transmission System Operators determine the commercial transmission capacity that can be implicitly traded in a zonal day-ahead market. However, this entails a trade-off: higher commercial transmission capacities increase market efficiency, affecting the electricity market prices, but also increase redispatch costs, affecting the network tariff. The decision on the commercial transmission capacity should optimally balance day-ahead welfare and redispatch costs, but depends on the rules and regulated incentives enforced on the TSOs. A MinRAM criterion, i.e., imposing minima for the commercial transmission capacity, is a one-size-fits-all policy without variation in time and space that unlikely leads to optimal transmission capacity allocation and is hard to tune because regulators have incomplete information. Incentive regulation is an alternative policy instrument promoting welfare-maximizing commercial transmission capacities, robust against information asymmetry. We provide a set of mathematical conditions to properly design an incentive scheme that rewards price convergence and penalizes excessive redispatch costs. Therefore, this paper serves as a stepping stone towards tapping the full potential of cross-border trade in zonal markets for policymakers, regulators, TSOs and market participants. • Flow-based market coupling is prone to welfare losses because its performance depends on parameters, set by TSOs. • Regulatory oversight is important to stimulate welfare-optimal commercial transmission capacities. • MinRAM criteria could be useful, but are static by design and could lead to welfare losses. • Incentive regulation, if well designed, allows to consider the multiple objectives of TSOs. • Moreover, it can overcome the issue of information asymmetry between TSO and regulator. [ABSTRACT FROM AUTHOR]

The establishment of a long-term, cross-border market in which forward market coupling and bilateral contracts are developed in an integrated approach is instrumental for the European internal electricity market. We propose the joint energy and transmission right auction (JETRA) mechanism, developed by O'Neill et al., as a solution for long-term cross-border markets in Europe. The main contribution of this research lies in its examination of the underlying market structures for effective JETRA implementation. We compare the institutional setting, market rules, and grid modeling under nodal and zonal pricing systems, adapting JETRA to the flow-based market coupling (FBMC) mechanism that is currently implemented in the European day-ahead market. This adaptation reveals the inherent limitations of FBMC in supporting JETRA, in particular in the long-term auction. We also identify constraints posed by existing European market rules, particularly those that affect the application of multi-settlement rules and the effective timeframe of hedging instruments. In conclusion, our research suggests that transitioning from zonal to nodal pricing is essential for JETRA's effective implementation. Furthermore, a comprehensive market reform is required to seamlessly integrate long- and short-term markets. [ABSTRACT FROM AUTHOR]

Battery energy storage is becoming an important asset in modern power systems. Considering the market prices and battery storage characteristics, reserve provision is a tempting play fields for such assets. This paper aims at filling the gap by developing a mathematically rigorous model and applying it to the existing and future electricity market design in Europe. The paper presents a bilevel model for optimal battery storage participation in day-ahead energy market as a price taker, and reserve capacity and activation market as a price maker. It uses an accurate battery charging model to reliably represent the behavior of real-life lithium-ion battery storage. The proposed bilevel model is converted into a mixed-integer linear program by using the Karush–Kuhn–Tucker optimality conditions. The case study uses real-life data on reserve capacity and activation costs and quantities in German markets. The reserves activation quantities and activation prices are modeled by a set of credible scenarios in the lower-level problem. Finally, a sensitivity analysis is conducted to comprehend to what extent do battery storage bidding prices affect its overall profit. [ABSTRACT FROM AUTHOR]

The interdependence of electricity and natural gas is becoming a major energy policy and regulatory issue in all jurisdictions around the world. The increased role of gas fired plants in renewable-based electricity markets and the dependence on natural gas imports make this issue particular important for the European energy market. In this paper we provide a comprehensive combined analysis of electricity and natural gas infrastructure with an applied focus: We analyze three different scenarios of the long-term European decarbonization pathways, and analyze the interrelation between electricity and natural gas markets on investments in the long run and spatial aspects in the short run. [ABSTRACT FROM AUTHOR]

Abstract: Electricity systems models are software tools used to manage electricity demand and the electricity systems, to trade electricity and for generation expansion planning purposes. Various portfolios and scenarios are modelled in order to compare the effects of decision making in policy and on business development plans in electricity systems so as to best advise governments and industry on the least cost economic and environmental approach to electricity supply, while maintaining a secure supply of sufficient quality electricity. The modelling techniques developed to study vertically integrated state monopolies are now applied in liberalised markets where the issues and constraints are more complex. This paper reviews the changing role of electricity systems modelling in a strategic manner, focussing on the modelling response to key developments, the move away from monopoly towards liberalised market regimes and the increasing complexity brought about by policy targets for renewable energy and emissions. The paper provides an overview of electricity systems modelling techniques, discusses a number of key proprietary electricity systems models used in the USA and Europe and provides an information resource to the electricity analyst not currently readily available in the literature on the choice of model to investigate different aspects of the electricity system. [ABSTRACT FROM AUTHOR]

• Flow-based market coupling problem in spot electricity markets with zonal exchanges. • Hybrid network configuration, with a zonal market layer and a nodal physical layer. • Zonal portfolio offers submitted by participants and zonal market clearing prices. • Dynamic definition of generation shift keys avoiding inefficiencies of static GSKs. • The method is evaluated on a continental Europe power system case. A novel model for the solution of the flow-based market coupling problem in multi-zonal spot electricity markets with zonal exchanges is presented in this paper. The problem considers a hybrid network configuration, i.e. a zonal market layer with zonal portfolio offers / bids submitted by the participants and zonal market clearing prices, and a nodal physical layer with nodal representation of the transmission system flows and relevant constraints. The model provides the optimal supply / demand cleared quantities and zonal exchanges, endogenously bounded by grid physical constraints, e.g. branch physical limits. The model retains the intuitiveness of the zonal exchanges, namely exchanges are cleared only from low-price zones to high-price zones. The model exhibits a dynamic/optimal allocation of zonal to nodal volumes. This market setup is fully compliant with the current market design in Europe, where portfolio participation in spot market with zonal prices, intuitive exchanges and with nodal flow-based constraints is the preferred scheme of the European Commission based on Regulation 2015/1222. The model is compared in terms of overall social welfare, pricing and cleared exchanges with the currently applied approach in Europe plus a "tuning" model for the simulation of redispatching to avoid congestion in physical branches. A novel model for the solution of the flow-based market coupling problem in multi-zonal spot electricity markets with zonal exchanges is presented in this paper. The problem considers a hybrid network configuration, i.e. a zonal market layer with zonal portfolio offers / bids submitted by the participants and zonal market clearing prices, and a nodal physical layer with nodal representation of the transmission system flows and relevant constraints. The model provides the optimal supply / demand cleared quantities and zonal exchanges, endogenously bounded by grid physical constraints, e.g. branch physical limits. The model retains the intuitiveness of the zonal exchanges, namely exchanges are cleared only from low-price zones to high-price zones. The model exhibits a dynamic/optimal definition of generation shift keys. This market setup is fully compliant with the current market design in Europe, where portfolio participation in spot market with zonal prices, intuitive exchanges and with nodal flow-based constraints is the preferred scheme of the European Commission based on Regulation 2015/1222. The model is compared in terms of overall social welfare, pricing and cleared exchanges with the currently applied approach in Europe plus a "tuning" model for the simulation of redispatching to avoid congestion in physical branches. [ABSTRACT FROM AUTHOR]

In light of the advancing energy transition and an increasing amount of intermittent renewable energy to be integrated, flexibility from distributed energy resources will be key. In this paper, the Italian UVAM (Unità Virtuali Abilitate Miste, i.e., virtually aggregated mixed units) project, one of the biggest pilots in Europe to serve this purpose, is critically reviewed and mapped after two years of operation. The pilot is analyzed on a global level as well as the individual participant level. Based on the extensive analysis of actual market data, different strategies of participating companies to obtain capacity in accordance with the pilot project's design are identified. Furthermore, the specific bidding strategies of individual participating units on the balancing market are outlined. Alongside this, the overall pilot project's market integration, in terms of offered and accepted bids, is depicted. The thorough data analysis, therefore, serves as an input and fundamental building block for future electricity market modeling. Comprehending specific data from the coronavirus disease 2019 (COVID-19) pandemic, provides insights for future high renewable-energy scenarios. Based on the analysis findings, valuable deliverables are devised for both policy-makers and decision-makers who aim to leverage the flexibility potential of distributed resources. [ABSTRACT FROM AUTHOR]

This paper presents a set of policy recommendations for the market design of a future European electricity system characterized by a dominant share of renewable energy supply (RES), in line with the stated targets of European governments. We discuss the market failures that need to be addressed to accommodate RES in liberalized electricity markets, review the evolution of the EU's RES policy mechanisms, and summarize the key market impacts of variable RES to date. We then set out economic principles for wholesale market design and use these to develop our policy recommendations. Our analysis covers the value of interconnection and market integration, electricity storage, the design of RES support mechanisms, distributed generation and network tariffs, the pricing of electricity and flexibility as well as long-term contracting and risk management. [ABSTRACT FROM AUTHOR]

This paper compares the evolution of USA and European power markets and evaluates the suitability and future challenges of their designs in the context of the transition to a low-carbon power system. The analysis focuses on bidding formats (the way in which organized electricity markets allow participants to express their operational constraints) and pricing schemes (how agents recover their short-term costs from market prices). The radical evolution of the power mixes worldwide already experienced in the last decade and the larger one to come, with even greater shares of renewable energy and a more prominent role for storage resources, exposes limitations in current market designs. We develop an in-depth and comprehensive review of best practices from both sides of the Atlantic, and learning from them, we draw recommendations to evolve these market design elements. [ABSTRACT FROM AUTHOR]

National politicians in Europe have created independent regulatory agencies (IRAs) with significant powers over markets such as communications and energy. After delegation, they have engaged in institutional politicization of IRAs and undertaken numerous attempted or actual de‐delegations. Yet overall de‐delegation over the period 2000–2020 has been limited, as many de‐delegations have been abandoned, temporary or reversed, and also counterbalanced by extensions of IRA powers. The article examines different explanations for this pattern. It looks especially at Europeanization, which has operated through normative and particularly coercive mechanisms. EU coercion has involved threats of legal action, monitoring and enforcement of existing EU legal requirements, and EU legislation expanding IRA powers and protection. IRAs are more vulnerable to de‐delegation than trustee non‐majoritarian institutions because their position can be altered with simple legislative majorities. Yet even for such agents, the ability of national politicians to reverse delegation is constrained by multi‐level institutional settings. [ABSTRACT FROM AUTHOR]

Network constraints play a key role in the price finding mechanism for European Power Markets, but historical data is very sparse and usually insufficient for many quantitative applications. We reconstruct the constraints data, known as the Power Transmission Distribution Factors (PTDFs) and Remaining Available Margins (RAMs), by first recovering the underlying time dependent signals known as the Generation Shift Keys (GSKs) and Phase Angles (PAs), and the electricity grid characteristics, via a mathematical optimisation problem. This is solved by exploiting marginal convexity in certain subspaces via alternating minimisation. The GSKs and PAs are then mapped to the PTDFs and RAMs, using the grid structure. Our reconstruction achieves in-sample relative errors of 22.3% and 15.9% for the PTDFs and RAMs respectively, while the out-of-sample ones are 25.4% and 18.1% respectively. We further show that our model outperforms the naive approach, and that the reconstructed GSKs and PAs recover specific structure. [ABSTRACT FROM AUTHOR]

Convex hull pricing is a well-documented method for coping with the non-existence of uniform clearing prices in electricity markets with non-convex costs and constraints. We revisit primal and dual methods for computing convex hull prices, and discuss the positioning of existing approximation methods in this taxonomy. We propose a dual decomposition algorithm known as the Level Method and we adapt the basic algorithm to the specificities of convex hull pricing. We benchmark its performance against a column generation algorithm that has recently been proposed in the literature. We provide empirical evidence about the favorable performance of our algorithm on large test instances based on PJM and Central Europe. [ABSTRACT FROM AUTHOR]

A novel experimental approach of inter- and intramodel comparisons is conducted with five power market models to give recommendations for modelers working on decarbonization pathways of Europe until 2050. The experiments investigate the impact of model type (optimization vs. simulation), planning horizon (intertemporal vs. myopic), temporal resolution (8760 vs. 384 h), and spatial resolution (28 countries vs. 12 mega-regions). The model type fundamentally determines the evolution of capacity expansion. Planning horizon (assumed foresight of firms) plays a minor role for scenarios with high carbon prices. For low carbon prices in turn, results from myopic models deviate considerably from those of intertemporal models. Lower temporal and spatial resolutions foster wind power via storage and via neglected transmission boundaries, respectively. Using simulation instead of optimization frameworks, a shorter planning horizon of firms, or lower temporal and spatial resolutions might be necessary to reduce the computational complexity. This paper delivers recommendations on how to limit the discrepancies in such cases. • Comparison of five power market models with harmonized input data and model features. • Evaluating the role of model type, planning horizon, spatial and temporal resolution. • Model type decisive for investment decisions. • Myopic modeling hardly changes variable renewable energy expansion but might favor conventional power plants. • Spatial and temporal resolution crucial for ease of variable renewable energy integration. [ABSTRACT FROM AUTHOR]

A common feature to electricity markets with derivative contracts is that the traded contracts are almost only futures and that they are traded multiple times the overall electricity demand. To understand why this occurs in practice, we study the efficiency of risk aligning in the competitive energy industry through derivative contract trading. We derive conditions that need to hold for a contract to provide the most efficient risk aligning, among all possible derivative contracts imaginable. We develop a game‐theoretical model that includes multiple competing producers and retailers whose decision‐makers are heterogeneous in their risk preferences that are captured using mean‐variance utilities. We derive closed‐form equilibrium quantities for the exchanged contracts and contract prices. We show using a simplified setup that, under an inelastic spot price, the optimal quantity and the price of the traded futures contract are driven by the proportion of the electricity spot price that retailers pass down to the consumers. In particular, this proportion impacts who are the buyers and the sellers of the contracts, what quantities of contracts are traded, and at what price the contracts are traded. We apply the model to the German electricity market and show that the conditions for guaranteeing a futures contract to be the most efficient risk aligning contract hold approximately. Our result can explain the dominance of futures contract trading in the energy industry and also the counter‐intuitively large quantity of traded futures, which exceeds multiple times the supplied quantity of electricity. Our results can aid decision‐makers in deciding on the types, amounts, and prices of contracts to trade. For market regulators, our results are helpful in providing understanding regarding the contract trading behavior on the market. [ABSTRACT FROM AUTHOR]

[Display omitted] • Methodology to optimize commercial EV pool composition for V2G services. • Simulation of EV pooling to provide balancing power (FCR) and arbitrage trading. • Optimized pool composition enables an increase in revenue per EV of up to 7-fold. • Showcase analysis of battery-specific costs arising from degradation in V2G. The market ramp-up of electromobility is shifting vehicle-to-grid (V2G) issues into the focus of research and industry. Electric vehicles (EVs) have the potential to support the trend towards renewable energies in their role as storage units during idle times. To participate in balancing power and energy markets, EVs are pooled via aggregators. Instead of a random composition, aggregators can smartly compose their pools and add only those vehicles that actually contribute to the pool's performance, gaining advantages over competitors. The optimization methods presented in this paper form optimized pool combinations based on the power and energy capability profiles of commercial EVs. Genetic algorithms are used to determine the revenues of the possible pools per participating EV. The use cases analyzed are the provision of balancing power on the frequency containment reserve (FCR) market of Central Europe and energy arbitrage trading on the European power exchange intraday continuous and day-ahead auction spot markets. The results show that through smart pool composition, an aggregator can increase revenue per vehicle by up to seven-fold across the markets compared to randomly assembled pools. In the Central European market, for example, the potential V2G revenues on the FCR market (380 €) exceeded those of arbitrage trading (28 € − 203 €) in 2020. In a simulation, we show the increased degradation of the vehicle battery in V2G operation compared to sole use for mobility with a smart charging strategy. However, the additional revenue can make V2G financially worthwhile, depending on costs for measuring equipment, bidirectional charging stations, and aggregator costs. [ABSTRACT FROM AUTHOR]

Abstract: The increase in PV (photovoltaic) capacities in Germany had since 2011 on some days already significant impacts on spot market prices at the German electricity exchange. The core objective of this paper is to investigate the possible effects of a further uptake of PV on the prices in electricity markets. We analyze two major effects: (i) the direct impact of PV at specific times of the year when PV shifts the supply curve of conventional electricity virtually out of the market, leading to temporarily very low market prices close to Zero; (ii) the indirect impact of PV (and wind) on the costs at which fossil capacities are offered at times when renewable energy sources are scarce. The major effects of these developments on the electricity markets will be: (i) a much higher price volatility from hour-to-hour and day-to-day; (ii) higher prices for electricity from fossil capacities and storage technologies for balancing the intermittent renewable generation; and (iii) growth of balancing markets and intensified competition at the level of decentralized balancing organizations. [Copyright &y& Elsevier]

Abstract: Hydrogen has a wide range of applications. In view of the environmental benefits, hydrogen can be produced by decarbonized means. When alkaline electrolysis is the selected process, extra value is offered by flexible operation that could bring both; an opportunity to reduce the cost of hydrogen produced (by consuming electricity during off-peak hours, and stopping the process during peak hours) and also a complementary tool to help balancing of the electric system. This paper assesses the profitability of market-driven operation for three different markets: France, Germany and Spain, with an analysis on the spot market. The market that exhibits the biggest potential in terms of profitability thanks to flexible operation is the French one, for each studied year. France is also the country that has the smallest installed renewable capacity amongst three considered countries. The gain on the hydrogen production cost allowed by the optimization is less than 3%. Hence, market-driven operation does not seem highly favourable to valorize fluctuating hydrogen production, when only the market price opportunities are considered. The balancing tool provided by the electrolysis system needs to be specifically valorized, in order to make flexible operation profitable. [Copyright &y& Elsevier]

The 'Clean Energy for All Europeans' legislative package places citizens and communities at the heart of the European energy policy by promoting local energy generation, consumption and trading. As only recently energy communities were formally defined in the European regulatory framework, the literature on energy community business models is still scattered and a clear systematization of community arrangements is missing. This paper aims to provide a comprehensive view of the prevailing and emergent energy communities business models, focusing on the value proposition offered by these initiatives. Community projects across Europe are analyzed and eight community business model archetypes are identified having the current European regulatory framework as background. The Business Model Canvas and the Lean Canvas frameworks are used to characterize and compare these archetypes. The main differences between business models are examined to highlight the most relevant strengths and barriers for energy community development. This analysis revealed the dominance of traditional self-consumption place-based communities, while business models involving differentiated services as demand flexibility, aggregation, energy efficiency and electric mobility are still scarce. However, the research around novel business models must be strengthened as they are expected to become crucial in upholding energy communities as key players in the energy transition and foster the regulatory framework evolution. • A comprehensive review of energy community business models is presented. • Eight business model archetypes are identified based on energy community drivers. • The Business Model Canvas and Lean Canvas are used to characterize business models. • The internal electricity market directive offers an attractive setting for novel business models. [ABSTRACT FROM AUTHOR]

• The electricity market in Europe is based on a zonal system. • A minimum of 70% of the cross-zonal capacity will have to be available for trade. • Such a minimum threshold could decrease the socio-economic welfare. • A smart redispatch is needed to avoid a decrease of the socio-economic welfare. The current organization of the internal electricity market in Europe relies on a zonal market system: the European power system is divided in bidding zones, electricity trades within a bidding zone can occur in an unconstrained manner, while electricity trades between bidding zones are limited by cross-zonal capacities. Two approaches can be used to calculate and allocate cross-zonal capacity: the coordinated Net Transmission Capacity (NTC) approach or the flow-based approach. In Central Western Europe, the flow-based approach is implemented for the day-ahead market since 2015. To avoid undue discrimination between internal and cross-border power exchanges, a minimum threshold of 70% on the cross-zonal capacity available for trade will be enforced in a near future. Such a threshold could significantly impact the socio-economic welfare and its distribution between the various actors. However, no assessment of the impacts of such a threshold has been performed so far, in particular because no convincing approach exists to perform such an assessment (e.g. security constraints and redispatch neglected). This paper develops such an approach and demonstrates its applicability on a case study, in order to assess the impact of a minimum threshold on cross-zonal capacity in a flow-based market. [ABSTRACT FROM AUTHOR]

The single imbalance pricing is an emerging mechanism in European electricity markets where all positive and negative imbalances are settled at a unique price. This real-time scheme thereby stimulates market participants to deviate from their schedule to restore the power system balance. However, exploiting this market opportunity is very risky due to the extreme volatility of the real-time power system conditions. In order to address this issue, we implement a new tailored deep-learning model, named encoder-decoder, to generate improved probabilistic forecasts of the imbalance signal, by efficiently capturing its complex spatio-temporal dynamics. The predicted distributions are then used to quantify and optimize the risk associated with the real-time participation of market players, acting as price-makers, in the imbalance settlement. This leads to an integrated forecast-driven strategy, modeled as a robust bi-level optimization. Results show that our probabilistic forecaster achieves better performance than other state of the art tools, and that the subsequent risk-aware robust dispatch tool allows finding a tradeoff between conservative and risk-seeking policies, leading to improved economic benefits. Moreover, we show that the model is computationally efficient and can thus be incorporated in the very-short-term dispatch of market players with flexible resources. [ABSTRACT FROM AUTHOR]

Integrating national markets is a major policy target in the European energy market. Yet, wholesale prices for electricity still differ significantly. Whether these price differences are caused only by limited interconnector capacities or also by lack of cross-border competition is an open question. To address this question, we develop a new approach to determine to which extent price differences stem from limited participation in cross-border trade. We derive a theoretical integration benchmark, using Grossman's (1976) notion of rational expectations equilibrium. We compare the benchmark to data from European electricity markets. The data reject the integration hypothesis and indicate that well-informed traders do not engage in cross-border trade. [ABSTRACT FROM AUTHOR]

The deregulation of the European power market brings new sales prospects for the power-suppliers as well as an appreciable increase of entrepreneurial risks. In order to handle the novel price- and volume-risks, the optimization of decision-making under uncertain boundary conditions is of essential interest. The former task of resource management in energy-supply was the minimization of costs for the fulfillment of a foreseeable power-request at long-ranging conditions of pricing. Now a multicriterial optimization problem arises: simultaneous minimization of cost and risk. In the last years a number of power-exchanges have been established where power is physically traded day-ahead and derivatively as future contracts. Furthermore, financial power-derivatives like Options, Caps, Floors or Swaps are traded bilaterial in the so called over-the-counter market. A serious question is how to use different physical contracts and financial derivatives in an optimal way to protect a power purchase portfolio against market risks. Facing this question, a multicriterial linear stochastic optimization model has been developed. It is based on scenarios for the market price, generated by Monte­Carlo-simulation that uses a mean-reversion market model calibrated for the German power spot-market. The different optimization criteria are merged into a single objective by a weighted summation. Individual risk aversion is considered by the coefficients of the weighted sum. The model is adapted to resolvability by Benders­Decomposition in a way that even a larger number of optimizations with different coefficients of the weighted sum can be solved in acceptable time giving an idea of the shape of the efficiency-frontier. Nevertheless all important microeconomics features have been taken into account. [ABSTRACT FROM AUTHOR]

To identify the trends in new flexibility markets, a set of market and aggregator platforms were selected and compared. The analyzed initiatives are relevant to consider alternative designs for European electricity markets. This review proposes a common methodology for analyzing these market models by comparing their description, market structure, market timing, and implementation. Furthermore, a range of policy implications and future research directions towards implementing these markets are presented. The results provide compelling evidence that the new market models represent a promising business with technical and economic justification, as they incentivize the uptake of flexibility from distributed resources by providing services to Distribution System Operators (DSOs) in coordination with Transmission System Operators (TSOs). Moreover, the interactions between these new market platforms and existing markets are of particular interest, and the contributions from aggregator platforms are also relevant to enhance the political vision of empowering the customers through their active participation in markets. [ABSTRACT FROM AUTHOR]

Nowadays, the payment scheme of European Day-Ahead Market is based on the market clearing price by running the Pan-European Hybrid Electricity Market Integration Algorithm. However, this conventional payment scheme is challenging because of the non-convexity and the short computation time requirement. Thus, the aim of this work is to propose a new clearing model in order to mitigate this challenge. The model is based on make-whole payment mechanism and it includes two major steps: (i) maximizing social welfare and (ii) achieving a Walrasian equilibrium by the "minimum-uplift approach". The proposed model is validated and investigated by two case studies: one is an artificially created Day-Ahead Market session containing all type of bids encountered in Europe and containing a very large number of bids to stress the algorithm and the other is a reduced, but realistic, model of European market where real data from February to December of 2017 were considered. The tests show a consistent improvement of the numerical performances of the proposed model with respect to the conventional one while the economic performance is not altered, but is slightly improved. Moreover, because the tests are based on real data during a long period of time, the results show that proposed model is very promising for the real application. [ABSTRACT FROM AUTHOR]